Improving Small Sample Properties of the Empirical Likelihood Estimation
We propose to use a simple modification of the maximum empirical likelihood (MEL) method for estimating structural equation in econometrics. The modified estimator improves both the asymptotic bias and the mean squared error of the MEL estimator in the orders of O(n -1) and O(n -2), respectively, at the same time. It also improves the asymptotic bias of the generalized method of moments (GMM) estimation (or the estimating equation (EE) method) significantly when there are many instruments in the econometric literatures.
|Date of creation:||Nov 2002|
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- Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2004.
"Empirical Likelihood-Based Inference in Conditional Moment Restriction Models,"
Econometric Society, vol. 72(6), pages 1667-1714, November.
- Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2001. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," CIRJE F-Series CIRJE-F-124, CIRJE, Faculty of Economics, University of Tokyo.
- Naoto Kunitomo & Yukitoshi Matsushita, 2003. "On Finite Sample Distributions of the Empirical Likelihood Estimator and the GMM Estimator," CIRJE F-Series CIRJE-F-200, CIRJE, Faculty of Economics, University of Tokyo.
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
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